Safe Motion Planning and Control Framework for Automated Vehicles with Zonotopic TRMPC

Model mismatches can cause multi-dimensional uncertainties for the receding horizon control strategies of automated vehicles(AVs).The uncertainties may lead to potentially hazardous behaviors when the AV tracks ideal trajectories that are individually optimized by the AV's planning layer.To address this issue,this study proposes a safe motion planning and control(SMPAC)framework for AVs.For the control layer,a dynamic model including multi-dimensional uncertainties is established.A zonotopic tube-based robust model predictive control scheme is proposed to constrain the uncertain system in a bounded minimum robust positive invariant set.A flexible tube with varying cross-sections is constructed to reduce the controller conservatism.For the planning layer,a concept of safety sets,representing the geometric boundaries of the ego vehicle and obstacles under uncertainties,is proposed.The safety sets provide the basis for the subsequent evaluation and ranking of the generated trajectories.An efficient collision avoidance algorithm decides the desired trajectory through the intersection detection of the safety sets between the ego vehicle and obstacles.A numerical simulation and hardware-in-the-loop experiment validate the effectiveness and real-time performance of the SMPAC.The result of two driving scenarios indicates that the SMPAC can guarantee the safety of automated driving under multi-dimensional uncertainties.

基于Leap Motion手势识别的三维交互系统

随着虚拟交互技术的发展,人们迈入了“体验式经济时代”,消费者越来越关注个性体验,因此,基于Leap Motion手势识别设备,设计了一种三维虚拟室内交互系统。该系统以Unity3D作为开发工具,Leap Motion作为硬件平台,结合C#语言进行脚本的编译,利用3ds Max平台对室内进行场景搭建,通过Unity3D工具将组件整合,设计了七种手势,使用Leap Motion硬件设备对场景中物体进行各种不同的操作。经试验表明,该系统实现了用户与场景中物体的交互能力,可以应用在室内装修和设计等方面,增强人们的体验感与趣味性。

Pulses in ground motions identified through surface partial matching and their impact on seismic rocking consequence

In seismology and earthquake engineering,it is fundamental to identify and characterize the pulse-like features in pulse-type ground motions.To capture the pulses that dominate structural responses,this study establishes congruence and shift relationships between response spectrum surfaces.A similarity search between spectrum surfaces,supplemented with a similarity search in time series,has been applied to characterize the pulse-like features in pulse-type ground motions.The identified pulses are tested in predicting the rocking consequences of slender rectangular blocks under the original ground motions.Generally,the prediction is promising for the majority of the ground motions where the dominant pulse is correctly identified.

Quantitative analysis of the morphing wing mechanism of raptors:IMMU-based motion capture system and its application on gestures of a Falco peregrinus

This paper presented a novel tinny motion capture system for measuring bird posture based on inertial and magnetic measurement units that are made up of micromachined gyroscopes, accelerometers, and magnetometers. Multiple quaternion-based extended Kalman filters were implemented to estimate the absolute orientations to achieve high accuracy.Under the guidance of ornithology experts, the extending/contracting motions and flapping cycles were recorded using the developed motion capture system, and the orientation of each bone was also analyzed. The captured flapping gesture of the Falco peregrinus is crucial to the motion database of raptors as well as the bionic design.

Monitoring absolute vertical land motions and absolute sea-level changes from GPS and tide gauges data over French Polynesia

In this study,we estimate the absolute vertical land motions at three tidal stations with collocated Global Navigation Satellite System(GNSS)receivers over French Polynesia during the period 2007-2020,and obtain,as ancillary results,estimates of the absolute changes in sea level at the same locations.To verify our processing approach to determining vertical motion,we first modeled vertical motion at the International GNSS Service(IGS)THTI station located in the capital island of Tahiti and compared our estimate with previous independent determinations,with a good agreement.We obtained the following estimates for the vertical land motions at the tide gauges:Tubuai island,Austral Archipelago-0.92±0.17 mm/yr,Vairao village,Tahiti Iti:-0.49±0.39 mm/yr,Rikitea,Gambier Archipelago-0.43±0.17 mm/yr.The absolute variations of the sea level are:Tubuai island,Austral Archipelago 5.25±0.60 mm/yr,Vairao village,Tahiti Iti:3.62±0.52 mm/yr,Rikitea,Gambier Archipelago 1.52±0.23 mm/yr.We discuss these absolute values in light of the values obtained from altimetric measurements and other means in French Polynesia.

A progressive framework for rotary motion deblurring

The rotary motion deblurring is an inevitable procedure when the imaging seeker is mounted in the rotating missiles.Traditional rotary motion deblurring methods suffer from ringing artifacts and noise,especially for large blur extents.To solve the above problems,we propose a progressive rotary motion deblurring framework consisting of a coarse deblurring stage and a refinement stage.In the first stage,we design an adaptive blur extents factor(BE factor)to balance noise suppression and details reconstruction.And a novel deconvolution model is proposed based on BE factor.In the second stage,a triplescale deformable module CNN(TDM-CNN)is designed to reduce the ringing artifacts,which can exploit the 2D information of an image and adaptively adjust spatial sampling locations.To establish a standard evaluation benchmark,a real-world rotary motion blur dataset is proposed and released,which includes rotary blurred images and corresponding ground truth images with different blur angles.Experimental results demonstrate that the proposed method outperforms the state-of-the-art models on synthetic and real-world rotary motion blur datasets.The code and dataset are available at https://github.com/JinhuiQin/RotaryDeblurring.

High-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer based on probability density evolution method

This paper proposed an efficient research method for high-dimensional uncertainty quantification of projectile motion in the barrel of a truck-mounted howitzer.Firstly,the dynamic model of projectile motion is established considering the flexible deformation of the barrel and the interaction between the projectile and the barrel.Subsequently,the accuracy of the dynamic model is verified based on the external ballistic projectile attitude test platform.Furthermore,the probability density evolution method(PDEM)is developed to high-dimensional uncertainty quantification of projectile motion.The engineering example highlights the results of the proposed method are consistent with the results obtained by the Monte Carlo Simulation(MCS).Finally,the influence of parameter uncertainty on the projectile disturbance at muzzle under different working conditions is analyzed.The results show that the disturbance of the pitch angular,pitch angular velocity and pitch angular of velocity decreases with the increase of launching angle,and the random parameter ranges of both the projectile and coupling model have similar influence on the disturbance of projectile angular motion at muzzle.

Adaptive Space Expansion for Fast Motion Planning

The sampling process is very inefficient for sam-pling-based motion planning algorithms that excess random sam-ples are generated in the planning space.In this paper,we pro-pose an adaptive space expansion(ASE)approach which belongs to the informed sampling category to improve the sampling effi-ciency for quickly finding a feasible path.The ASE method enlarges the search space gradually and restrains the sampling process in a sequence of small hyper-ellipsoid ring subsets to avoid exploring the unnecessary space.Specifically,for a con-structed small hyper-ellipsoid ring subset,if the algorithm cannot find a feasible path in it,then the subset is expanded.Thus,the ASE method successively does space exploring and space expan-sion until the final path has been found.Besides,we present a particular construction method of the hyper-ellipsoid ring that uniform random samples can be directly generated in it.At last,we present a feasible motion planner BiASE and an asymptoti-cally optimal motion planner BiASE*using the bidirectional exploring method and the ASE strategy.Simulations demon-strate that the computation speed is much faster than that of the state-of-the-art algorithms.The source codes are available at https://github.com/shshlei/ompl.

Generative adversarial networks based motion learning towards robotic calligraphy synthesis

Robot calligraphy visually reflects the motion capability of robotic manipulators.While traditional researches mainly focus on image generation and the writing of simple calligraphic strokes or characters,this article presents a generative adversarial network(GAN)-based motion learning method for robotic calligraphy synthesis(Gan2CS)that can enhance the efficiency in writing complex calligraphy words and reproducing classic calligraphy works.The key technologies in the proposed approach include:(1)adopting the GAN to learn the motion parameters from the robot writing operation;(2)converting the learnt motion data into the style font and realising the transition from static calligraphy images to dynamic writing demonstration;(3)reproducing high-precision calligraphy works by synthesising the writing motion data hierarchically.In this study,the motion trajectories of sample calligraphy images are firstly extracted and converted into the robot module.The robot performs the writing with motion planning,and the writing motion parameters of calligraphy strokes are learnt with GANs.Then the motion data of basic strokes is synthesised based on the hierarchical process of‘stroke-radicalpart-character’.And the robot re-writes the synthesised characters whose similarity with the original calligraphy characters is evaluated.Regular calligraphy characters have been tested in the experiments for method validation and the results validated that the robot can actualise the robotic calligraphy synthesis of writing motion data with GAN.

Influence of Brownian Motion, Thermophoresis and Magnetic Effects on a Fluid Containing Nanoparticles Flowing over a Stretchable Cylinder

The influence of Brownian motion and thermophoresis on a fluid containing nanoparticles flowing over a stretchable cylinder is examined.The classical Navier-Stokes equations are considered in a porous frame.In addition,the Lorentz force is taken into account.The controlling coupled nonlinear partial differential equations are transformed into a system of first order ordinary differential equations by means of a similarity transformation.The resulting system of equations is solved by employing a shooting approach properly implemented in MATLAB.The evolution of the boundary layer and the growing velocity is shown graphically together with the related profiles of concentration and temperature.The magnetic field has a different influence(in terms of trends)on velocity and concentration.

Secure Transmission of Compressed Medical Image Sequences on Communication Networks Using Motion Vector Watermarking

Medical imaging plays a key role within modern hospital management systems for diagnostic purposes.Compression methodologies are extensively employed to mitigate storage demands and enhance transmission speed,all while upholding image quality.Moreover,an increasing number of hospitals are embracing cloud computing for patient data storage,necessitating meticulous scrutiny of server security and privacy protocols.Nevertheless,considering the widespread availability of multimedia tools,the preservation of digital data integrity surpasses the significance of compression alone.In response to this concern,we propose a secure storage and transmission solution for compressed medical image sequences,such as ultrasound images,utilizing a motion vector watermarking scheme.The watermark is generated employing an error-correcting code known as Bose-Chaudhuri-Hocquenghem(BCH)and is subsequently embedded into the compressed sequence via block-based motion vectors.In the process of watermark embedding,motion vectors are selected based on their magnitude and phase angle.When embedding watermarks,no specific spatial area,such as a region of interest(ROI),is used in the images.The embedding of watermark bits is dependent on motion vectors.Although reversible watermarking allows the restoration of the original image sequences,we use the irreversible watermarking method.The reason for this is that the use of reversible watermarks may impede the claims of ownership and legal rights.The restoration of original data or images may call into question ownership or other legal claims.The peak signal-to-noise ratio(PSNR)and structural similarity index(SSIM)serve as metrics for evaluating the watermarked image quality.Across all images,the PSNR value exceeds 46 dB,and the SSIM value exceeds 0.92.Experimental results substantiate the efficacy of the proposed technique in preserving data integrity.

Underdetermined direction of arrival estimation with nonuniform linear motion sampling based on a small unmanned aerial vehicle platform

Uniform linear array(ULA)radars are widely used in the collision-avoidance radar systems of small unmanned aerial vehicles(UAVs).In practice,a ULA's multi-target direction of arrival(DOA)estimation performance suffers from significant performance degradation owing to the limited number of physical elements.To improve the underdetermined DOA estimation performance of a ULA radar mounted on a small UAV platform,we propose a nonuniform linear motion sampling underdetermined DOA estimation method.Using the motion of the UAV platform,the echo signal is sampled at different positions.Then,according to the concept of difference co-array,a virtual ULA with multiple array elements and a large aperture is synthesized to increase the degrees of freedom(DOFs).Through position analysis of the original and motion arrays,we propose a nonuniform linear motion sampling method based on ULA for determining the optimal DOFs.Under the condition of no increase in the aperture of the physical array,the proposed method obtains a high DOF with fewer sampling runs and greatly improves the underdetermined DOA estimation performance of ULA.The results of numerical simulations conducted herein verify the superior performance of the proposed method.

On a Compound Poisson Risk Model Perturbed by Brownian Motion with Variable Premium and Tail Dependence between Claims Amounts and Inter-Claim Time

This paper considers the compound Poisson risk model perturbed by Brownian motion with variable premium and dependence between claims amounts and inter-claim times via Spearman copula. It is assumed that the insurance company’s portfolio is governed by two classes of policyholders. On the one hand, the first class where the amount of claims is high, and on the other hand, the second class where the amount of claims is low, this difference in claim amounts has significant implications for the insurance company’s pricing and risk management strategies. When policyholders are in the first class, they pay an insurance premium of a constant amount c1 and when they are in the second class, the premium paid is a constant amount c2 such that c1 > c2. The nature of claims (low or high) is measured via random thresholds . The study in this work will focus on the determination of the integro-differential equations satisfied by Gerber-Shiu functions and their Laplace transforms in the risk model perturbed by Brownian motion with variable premium and dependence between claims amounts and inter-claim times via Spearman copula. .

Zeno and the Wrong Understanding of Motion—A Philosophical-Mathematical Inquiry into the Concept of Finitude as a Peculiarity of Infinity

In contrast to the solutions of applied mathematics to Zeno’s paradoxes, I focus on the concept of motion and show that, by distinguishing two different forms of motion, Zeno’s apparent paradoxes are not paradoxical at all. Zeno’s paradoxes indirectly prove that distances are not composed of extensionless points and, in general, that a higher dimension cannot be completely composed of lower ones. Conversely, lower dimensions can be understood as special cases of higher dimensions. To illustrate this approach, I consider Cantor’s only apparent proof that the real numbers are uncountable. However, his widely accepted indirect proof has the disadvantage that it depends on whether there is another way to make the real numbers countable. Cantor rightly assumes that there can be no smallest number between 0 and 1, and therefore no beginning of counting. For this reason he arbitrarily lists the real numbers in order to show with his diagonal method that this list can never be complete. The situation is different if we start with the largest number between 0 and 1 (0.999…) and use the method of an inverted triangle, which can be understood as a special fractal form. Here we can construct a vertical and a horizontal stratification with which it is actually possible to construct all real numbers between 0 and 1 without exception. Each column is infinite, and each number in that column is the starting point of a new triangle, while each row is finite. Even in a simple sine curve, we experience finiteness with respect to the y-axis and infinity with respect to the x-axis. The first parts of this article show that Zeno’s assumptions contradict the concept of motion as such, so it is not surprising that this misconstruction leads to contradictions. In the last part, I discuss Cantor’s diagonal method and explain the method of an inverted triangle that is internally structured like a fractal by repeating this inverted triangle at each column. The consequence is that we encounter two very different methods of counting. Vertically it is continuous, horizontally it is discrete. While Frege, Tarski, Cantor, Gödel and the Vienna Circle tried to derive the higher dimension from the lower, a procedure that always leads to new contradictions and antinomies (Tarski, Russell), I take the opposite approach here, in which I derive the lower dimension from the higher. This perspective seems to fail because Tarski, Russell, Wittgenstein, and especially the Vienna Circle have shown that the completeness of the absolute itself is logically contradictory. For this reason, we agree with Hegel in assuming that we can never fully comprehend the Absolute, but only its particular manifestations—otherwise we would be putting ourselves in the place of the Absolute, or even God. Nevertheless, we can understand the Absolute in its particular expressions, as I will show with the modest example of the triangle proof of the combined horizontal and vertical countability of the real numbers, which I developed in rejection of Cantor’s diagonal proof. .

Seismic Response Analysis of Steel Structure Isolation System Under Long-Period Seismic Motion

To analyze the seismic response of steel structure isolation systems under long-period seismic motion,a 9-story steel frame building was selected as the subject.Five steel structure finite element models were established using SAP2000.Response spectrum analysis was conducted on the seismic motion to determine if it adhered to the characteristics of long-period seismic motion.Modal analysis of each structural model revealed that the isolation structure significantly prolonged the structural natural vibration period and enhanced seismic performance.Base reactions and floor displacements of various structures notably increased under long-period seismic motion compared to regular seismic activity.Placing isolation bearings in the lower part of the structure proved more effective under long-period seismic motion.In seismic design engineering,it is essential to consider the impact of long-period seismic motion on structures and the potential failure of isolation bearings.

A Multi-Task Motion Generation Model that Fuses a Discriminator and a Generator

The human motion generation model can extract structural features from existing human motion capture data,and the generated data makes animated characters move.The 3D human motion capture sequences contain complex spatial-temporal structures,and the deep learning model can fully describe the potential semantic structure of human motion.To improve the authenticity of the generated human motion sequences,we propose a multi-task motion generation model that consists of a discriminator and a generator.The discriminator classifies motion sequences into different styles according to their similarity to the mean spatial-temporal templates from motion sequences of 17 crucial human joints in three-freedom degrees.And target motion sequences are created with these styles by the generator.Unlike traditional related works,our model can handle multiple tasks,such as identifying styles and generating data.In addition,by extracting 17 crucial joints from 29 human joints,our model avoids data redundancy and improves the accuracy of model recognition.The experimental results show that the discriminator of the model can effectively recognize diversified movements,and the generated data can correctly fit the actual data.The combination of discriminator and generator solves the problem of low reuse rate of motion data,and the generated motion sequences are more suitable for actual movement.

MPC-based Motion Planning and Control Enables Smarter and Safer Autonomous Marine Vehicles:Perspectives and a Tutorial Survey

Autonomous marine vehicles(AMVs)have received considerable attention in the past few decades,mainly because they play essential roles in broad marine applications such as environmental monitoring and resource exploration.Recent advances in the field of communication technologies,perception capability,computational power and advanced optimization algorithms have stimulated new interest in the development of AMVs.In order to deploy the constrained AMVs in the complex dynamic maritime environment,it is crucial to enhance the guidance and control capabilities through effective and practical planning,and control algorithms.Model predictive control(MPC)has been exceptionally successful in different fields due to its ability to systematically handle constraints while optimizing control performance.This paper aims to provide a review of recent progress in the context of motion planning and control for AMVs from the perceptive of MPC.Finally,future research trends and directions in this substantial research area of AMVs are highlighted.

Numerical Study on Aerodynamic Performance of Floating Dual-Rotor Wind Turbines in Heave and Surge Motions

Compared with the traditional wind turbine of a single rotor,dual-rotor wind turbines(DRWTs)have higher wind energy capture efficiency and a more complex structure.Therefore,the aerodynamic performance of the DRWT installed on the floating platform will be greatly affected by the motion caused by wind and wave loads.In this paper,5 MW and 750 kW single rotor wind turbines(SRWTs)are combined into a 5 MW-5 MW DRWT and a 5 MW-750 kW DRWT,and their power output and wake field characteristics in different motions are studied.The flow field is obtained by solving the Reynolds-averaged Navier–Stokes equation(RANS).The overset grid technique is employed to achieve the large-amplitude multiple-degree-of-freedom motion of the DRWT.The overall performance of the 5 MW single rotor wind turbine is determined by a numerical method.For the DRWTs,numerical results show that the surge motion and heave motion both have a negative effect on the power output of the DRWT.The surge motion is a critical factor that causes the power output of the DRWT to periodically change with motion.The average power output of the DRWT influenced by motion is lower than that of a DRWT with a fixed bottom.The surge motion significantly disturbs the wake of the DRWT due to the mutual interference between the upstream and downstream rotors.Under the influence of heave motion,low-velocity regions downstream of the blade tip are enhanced.This study indicates that attenuating the surge and heave motion of offshore DRWT is very significant for improving its efficiency and should be taken into consideration during the design procedure.

基于Leap Motion的手语识别算法优化

Leap Motion设备产生的数据在虚拟环境中可以进行手势识别。通过识别和跟踪用户的手来生成虚拟3D手部模型,从而获取手势信息。本文设计了一种基于隐马尔可夫模型(Hidden Markov Model,HMM)分类算法来学习从Leap Motion中所获取的手势信息的系统,根据手势特征的重要性赋予不同权值,可进一步提高分类准确率,实现手语信息的识别输入。测试结果表明,识别准确率为86.1%,手语打字输入识别速度为每分钟13.09个字符,可显著提高聋哑人与正常人之间沟通的便捷性。

Vision-based fatigue crack detection using global motion compensation and video feature tracking

Fatigue cracks that develop in civil infrastructure such as steel bridges due to repetitive loads pose a major threat to structural integrity.Despite being the most common practice for fatigue crack detection,human visual inspection is known to be labor intensive,time-consuming,and prone to error.In this study,a computer vision-based fatigue crack detection approach using a short video recorded under live loads by a moving consumer-grade camera is presented.The method detects fatigue crack by tracking surface motion and identifies the differential motion pattern caused by opening and closing of the fatigue crack.However,the global motion introduced by a moving camera in the recorded video is typically far greater than the actual motion associated with fatigue crack opening/closing,leading to false detection results.To overcome the challenge,global motion compensation(GMC)techniques are introduced to compensate for camera-induced movement.In particular,hierarchical model-based motion estimation is adopted for 2D videos with simple geometry and a new method is developed by extending the bundled camera paths approach for 3D videos with complex geometry.The proposed methodology is validated using two laboratory test setups for both in-plane and out-of-plane fatigue cracks.The results confirm the importance of motion compensation for both 2D and 3D videos and demonstrate the effectiveness of the proposed GMC methods as well as the subsequent crack detection algorithm.